Can LLM agents actually discover hidden rules by interacting?
Rohan Paul Twitter · Rohan Paul (@rohanpaul_ai) · 2026-06-22
Research shared by Rohan Paul finds that LLM agents fail to reliably discover hidden rules through interaction, with performance degrading rapidly as environmental complexity increases because LLMs cannot build stable internal world models from accumulating evidence.
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Extraction
Topics: llm-agentsworld-modelingreasoningai-limitations
Claims
- LLM agents can sometimes discover hidden rules in simple environments but degrade rapidly as complexity grows.
- LLMs often cannot convert accumulating evidence into a stable internal model of an environment.
- The gap between LLM agent performance and required capability widens as hidden-world complexity increases.
Key quotes
The more complicated the hidden world gets, the faster AI agents fall behind.
LLMs often cannot turn growing evidence into a stable internal model.